It is a challenge to identify relevant information in a large set of documents, especially where the contents of the documents are not known in advance. Examples of such sets of documents include RSS or news feeds, incoming mail, discussion boards or blogs, or streams of chat, twitter tweets, or transcripts of audio.
There are existing techniques to sort information in large data feeds. These techniques use statistical methodologies to determine the information that is most popular with large numbers of users.
It would be desirable to develop a new sorting paradigm that focuses on personal relevance of information instead of the relevance of information to a large number of users.